{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T11:10:01Z","timestamp":1755861001314,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":49,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T00:00:00Z","timestamp":1730160000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["IIS-1907855, IIS-2203553"],"award-info":[{"award-number":["IIS-1907855, IIS-2203553"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,29]]},"DOI":"10.1145\/3678717.3691258","type":"proceedings-article","created":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T06:29:21Z","timestamp":1732256961000},"page":"561-564","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["On Splitting Raw Trajectories"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0221-3988","authenticated-orcid":false,"given":"Areeg","family":"Mostafa","sequence":"first","affiliation":[{"name":"University of Minnesota, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6686-1757","authenticated-orcid":false,"given":"Mohamed F.","family":"Mokbel","sequence":"additional","affiliation":[{"name":"University of Minnesota, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7648-1461","authenticated-orcid":false,"given":"Ana Elena","family":"Uribe","sequence":"additional","affiliation":[{"name":"University of Minnesota, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,11,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/3476311.3476329"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2666310.2666415"},{"key":"e_1_3_2_1_3_1","first-page":"274","volume-title":"Racoon: Rapid Contact Tracing of Moving Objects Using Smart Indexes. In Proceedings of the IEEE International Conference on Mobile Data Management, MDM","author":"Alseghayer R.","year":"2021","unstructured":"R. Alseghayer. Racoon: Rapid Contact Tracing of Moving Objects Using Smart Indexes. In Proceedings of the IEEE International Conference on Mobile Data Management, MDM, pages 274--276, June 2021."},{"key":"e_1_3_2_1_4_1","volume-title":"July","author":"Bracciale L.","year":"2014","unstructured":"L. Bracciale, M. Bonola, P. Loreti, G. Bianchi, R. Amici, and A. Rabuffi. CRAWDAD dataset roma\/taxi (v. 2014--07-17). Downloaded from https:\/\/ieee-dataport.org\/open-access\/crawdad-romataxi, July 2014."},{"key":"e_1_3_2_1_5_1","first-page":"33","volume":"3","author":"Buchin M.","year":"2011","unstructured":"M. Buchin, A. Driemel, M. J. van Kreveld, and V. Sacrist\u00e1n. Segmenting Trajectories: A Framework and Algorithms Using Spatiotemporal Criteria. Journal of Spatial Information Science, 3:33--63, 2011.","journal-title":"Journal of Spatial Information Science"},{"key":"e_1_3_2_1_6_1","first-page":"16","author":"Das R. D.","year":"2016","unstructured":"R. D. Das and S. Winter. Automated Urban Travel Interpretation: A Bottom-up Approach for Trajectory Segmentation. Sensors, 16, 2016.","journal-title":"Sensors"},{"key":"e_1_3_2_1_7_1","volume-title":"Mar.","author":"Dias D.","year":"2018","unstructured":"D. Dias and L. H. M. K. Costa. CRAWDAD dataset coppe-ufrj\/riobuses (v. 2018--03-19). Downloaded from https:\/\/ieee-dataport.org\/open-access\/crawdad-coppe-ufrjriobuses, Mar. 2018."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-47358-7_20"},{"key":"e_1_3_2_1_9_1","first-page":"58","volume-title":"EDBT\/ICDT Workshops","author":"Etemad M.","year":"2019","unstructured":"M. Etemad, A. S. J\u00fanior, A. Hoseyni, J. Rose, and S. Matwin. A Trajectory Segmentation Algorithm Based on Interpolation-based Change Detection Strategies. In EDBT\/ICDT Workshops, page 58, Mar. 2019."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2018.09.008"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30231-5_8"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3414274.3414491"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3356995.3364536"},{"issue":"3","key":"e_1_3_2_1_14_1","first-page":"4","article-title":"Value Creation from Massive Data in Transportation?","volume":"42","author":"Jensen C. S.","year":"2019","unstructured":"C. S.Jensen. Value Creation from Massive Data in Transportation? The Case of Vehicle Routing. IEEE Data Engineering Bulletin, 42(3):4--8, 2019.","journal-title":"The Case of Vehicle Routing. IEEE Data Engineering Bulletin"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.134"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274895.3274983"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/MDM52706.2021.00033"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3010022"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.14778\/2735461.2735466"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16115"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/956676.956691"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3003819.3003824"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.14778\/3476249.3476279"},{"key":"e_1_3_2_1_24_1","unstructured":"Kaggle. New York City Taxi Trip Duration. https:\/\/www.kaggle.com\/c\/nyc-taxi-trip duration\/data."},{"key":"e_1_3_2_1_25_1","unstructured":"Open Source Routing Machine (OSRM). http:\/\/project-osrm.org\/."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.14778\/3397230.3397248"},{"key":"e_1_3_2_1_27_1","volume-title":"Service Trajectory. Prediction Challenge. ECML PKDD 2015","author":"Taxi","year":"2015","unstructured":"Taxi Service Trajectory. Prediction Challenge. ECML PKDD 2015. https:\/\/archive.ics.uci.edu\/dataset\/339\/taxi+service+trajectory+prediction+challenge+ecml+pkdd+2015."},{"key":"e_1_3_2_1_28_1","unstructured":"SafeGraph. Your Partner in Places Data. https:\/\/www.safegraph.com\/."},{"key":"e_1_3_2_1_29_1","unstructured":"San Francisco Municipal Transportation Agency (SFMTA) - Transit Vehicle Location History (Current Year). https:\/\/data.sfgov.org\/Transportation\/SFMTA-Transit-Vehicle-Location-History-Current-Yea\/x344-v6h6\/about_data."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2015.462"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274895.3274916"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611975321.15"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3486898"},{"key":"e_1_3_2_1_34_1","unstructured":"T-Drive trajectory data sample. https:\/\/www.microsoft.com\/en-us\/research\/publication\/t-drive-trajectory-data-sample\/."},{"key":"e_1_3_2_1_35_1","unstructured":"Unacast. Build Better Products and Make Smarter Decisions with Real-world Location Data. https:\/\/www.unacast.com\/."},{"key":"e_1_3_2_1_36_1","unstructured":"Veraset. Your Trusted Partner for Mobility Data. https:\/\/www.veraset.com\/."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2019.05.028"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3300061.3300132"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1080\/21680566.2017.1386599"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3440207"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357907"},{"key":"e_1_3_2_1_42_1","first-page":"30380","volume-title":"Proceedings of the Annual Conference on Neural Information Processing Systems, NeurIPS","author":"Xue H.","year":"2021","unstructured":"H. Xue, F. D. Salim, Y. Ren, and N. Oliver. MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction. In Proceedings of the Annual Conference on Neural Information Processing Systems, NeurIPS, pages 30380--30391, Dec. 2021."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.89"},{"issue":"1","key":"e_1_3_2_1_44_1","first-page":"1","article-title":"SharedEdge: GPS-Free Fine-Grained Travel Time Estimation in State-Level Highway Systems. Proceedings of the ACM on Interactive, Mobile","volume":"2","author":"Yang Y.","year":"2018","unstructured":"Y. Yang, F. Zhang, and D. Zhang. SharedEdge: GPS-Free Fine-Grained Travel Time Estimation in State-Level Highway Systems. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(1):48:1--48:26, 2018.","journal-title":"Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2093973.2093980"},{"issue":"3","key":"e_1_3_2_1_46_1","first-page":"393","article-title":"Route Travel Time Estimation on a Road Network Revisited: Heterogeneity, Proximity, Periodicity and Dynamicity. Proceedings of the International Conference on Very Large Data Bases","volume":"16","author":"Yuan H.","year":"2023","unstructured":"H. Yuan, G. Li, and Z. Bao. Route Travel Time Estimation on a Road Network Revisited: Heterogeneity, Proximity, Periodicity and Dynamicity. Proceedings of the International Conference on Very Large Data Bases, PVLDB, 16(3):393--405, 2023.","journal-title":"PVLDB"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.200"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/2743025"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3378890"}],"event":{"name":"SIGSPATIAL '24: The 32nd ACM International Conference on Advances in Geographic Information Systems","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"],"location":"Atlanta GA USA","acronym":"SIGSPATIAL '24"},"container-title":["Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3678717.3691258","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3678717.3691258","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T10:38:37Z","timestamp":1755859117000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3678717.3691258"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,29]]},"references-count":49,"alternative-id":["10.1145\/3678717.3691258","10.1145\/3678717"],"URL":"https:\/\/doi.org\/10.1145\/3678717.3691258","relation":{},"subject":[],"published":{"date-parts":[[2024,10,29]]},"assertion":[{"value":"2024-11-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}